FCOS: Fully Convolutional One-Stage Object Detection

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 73,472

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1506.01497 · Cited by 70,812

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333

You Only Look Once: Unified, Real-Time Object Detection

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.91 · Cited by 53,803

Microsoft COCO: Common Objects in Context

Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460

Fully convolutional networks for semantic segmentation

Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834

Untitled work

(2016) · Cited by 31,590

Feature Pyramid Networks for Object Detection

Lin, T.-Y., Dollar, P., Girshick, R., He, K., Hariharan, B., & Belongie, S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.106 · Cited by 30,939

Focal Loss for Dense Object Detection

Lin, T.-Y., Goyal, P., Girshick, R., He, K., & Dollar, P. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.324 · Cited by 30,581

An Improved YOLOv5s Fire Detection Model

Dou, Z., Zhou, H., Liu, Z., Hu, Y., Wang, P., Zhang, J., Wang, Q., Chen, L., Diao, X., & Li, J. (2023) · Fire Technology · doi:10.1007/s10694-023-01492-7 · Cited by 50

An object detection algorithm based on infrared-visible dual modal feature fusion

Hou, Z., Yang, C., Sun, Y., Ma, S., Yang, X., & Fan, J. (2024) · Infrared Physics & Technology · doi:10.1016/j.infrared.2023.105107 · Cited by 49

Understanding Negative Proposals in Generic Few-Shot Object Detection

Yan, B., Lang, C., Cheng, G., & Han, J. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3367666 · Cited by 49

SAR Ship Detection Based on Explainable Evidence Learning Under Intraclass Imbalance

Liu, Y., Yan, G., Ma, F., Zhou, Y., & Zhang, F. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3373668 · Cited by 49

Preprocessing Enhanced Image Compression for Machine Vision

Lu, G. S., Ge, X., Zhong, T., Hu, Q., & Geng, J. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3441049 · Cited by 68

Attention R-CNN for Accident Detection

Le, T.-N., Ono, S., Sugimoto, A., & Kawasaki, H. (2020) · IEEE Intelligent Vehicles Symposium · doi:10.1109/iv47402.2020.9304730 · Cited by 49

Scene Text Retrieval via Joint Text Detection and Similarity Learning

Wang, H., Bai, X., Yang, M., Zhu, S., Wang, J., & Liu, W. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00453 · Cited by 50

Composing Photos Like a Photographer

Hong, C., Du, S., Xian, K., Lü, H., Cao, Z., & Zhong, W. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00698 · Cited by 50

Oriented Ship Detection Based on Strong Scattering Points Network in Large-Scale SAR Images

Sun, Y., Sun, X., Wang, Z., & Fu, K. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3130117 · Cited by 48

A Source-Free Domain Adaptive Polyp Detection Framework With Style Diversification Flow

Liu, X., & Yuan, Y. (2022) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2022.3150435 · Cited by 48

Attention-Guided Multitask Convolutional Neural Network for Power Line Parts Detection

Zhang, H., Wu, L., Chen, Y., Chen, R., Kong, S., Wang, Y., Hu, J., & Wu, Q. M. J. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3162615 · Cited by 48

VAMYOLOX: An Accurate and Efficient Object Detection Algorithm Based on Visual Attention Mechanism for UAV Optical Sensors

Yang, Y., Gao, X., Wang, Y., & Song, S. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3219199 · Cited by 48

Learning Local-Global Contextual Adaptation for Multi-Person Pose Estimation

Xue, N., Wu, T., Xia, G.-S., & Zhang, L. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01272 · Cited by 47

1 st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results

Kiefer, B., Kristan, M., Perš, J., Žust, L., Poiesi, F., Andrade, F. A. A., Bernardino, A. J. M., Dawkins, M., Raitoharju, J., Quan, Y., et al. (2023) · IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) · doi:10.1109/wacvw58289.2023.00033 · Cited by 54

YOLOLens: A Deep Learning Model Based on Super-Resolution to Enhance the Crater Detection of the Planetary Surfaces

Grassa, R. L., Cremonese, G., Gallo, I., Re, C., & Martellato, E. (2023) · Remote Sensing · doi:10.3390/rs15051171 · Cited by 48

FPANet: feature pyramid attention network for crowd counting

Zhai, W., Gao, M., Li, Q., Jeon, G., & Anisetti, M. (2023) · Applied Intelligence · doi:10.1007/s10489-023-04499-3 · Cited by 48

Gaussian similarity-based adaptive dynamic label assignment for tiny object detection

Fu, R., Chen, C., Yan, S. Z., Heidari, A. A., Wang, X., Escorcia‐Gutierrez, J., Mansour, R. F., & Chen, H. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126285 · Cited by 50

YOLO*C — Adding context improves YOLO performance

Oreški, G. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126655 · Cited by 56

Discriminative features enhancement for low-altitude UAV object detection

Huang, S., Ren, S., Wu, W. Y., & Liu, Q. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.110041 · Cited by 48

EdaDet: Open-Vocabulary Object Detection Using Early Dense Alignment

Shi, C., & Yang, S. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01441 · Cited by 53

Action Sensitivity Learning for Temporal Action Localization

Shao, J., Wang, X., Quan, R., Zheng, J., Jiang, Y., & Yang, Y. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01238 · Cited by 52

Automated pavement detection and artificial intelligence pavement image data processing technology

Shang, J., Zhang, A. A., Dong, Z., Zhang, H., & He, A. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105797 · Cited by 48

NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection

Li, Y., Pang, Y., Shen, J., Cao, J., & Shao, L. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01336 · Cited by 47

Hier R-CNN: Instance-Level Human Parts Detection and A New Benchmark

Yang, L., Song, Q., Wang, Z., Hu, M., & Liu, C. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3029901 · Cited by 48

Breast mass detection in digital mammography based on anchor-free architecture

Cao, H., Pu, S., Tan, W., & Tong, J. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106033 · Cited by 52

Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance

Carranza-García, M., Lara-Benítez, P., García–Gutiérrez, J., & Riquelme, J. C. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.04.001 · Cited by 50

Inception Convolution with Efficient Dilation Search

Liu, J., Li, C., Liang, F., Chen, L., Sun, M., Yan, J., Ouyang, W., & Xu, D. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01132 · Cited by 48

Variational Pedestrian Detection

Zhang, Y., He, H., Li, J., Li, Y., See, J., & Lin, W. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01145 · Cited by 48

Real-Time Robotic Multigrasp Detection Using Anchor-Free Fully Convolutional Grasp Detector

Wu, Y., Zhang, F., & Fu, Y. (2021) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2021.3135629 · Cited by 48

ACE: Anchor-Free Corner Evolution for Real-Time Arbitrarily-Oriented Object Detection

Dai, P., Yao, S., Li, Z., Zhang, S., & Cao, X. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3167919 · Cited by 47

An accurate detection and segmentation model of obscured green fruits

Liu, M., Jia, W., Wang, Z., Niu, Y., Yang, X., & Ruan, C. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2022.106984 · Cited by 47

Relation Matters: Foreground-aware Graph-based Relational Reasoning for Domain Adaptive Object Detection

Chen, C., Li, J., Zhou, H.-Y., Han, X., Huang, Y., Ding, X., & Yu, Y. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3179445 · Cited by 49

Automatic Detection and Identification of Defects by Deep Learning Algorithms from Pulsed Thermography Data

Fang, Q., Ibarra‐Castanedo, C., Garrido, I., Duan, Y.-X., & Maldague, X. (2023) · Sensors · doi:10.3390/s23094444 · Cited by 48

Threatening Patch Attacks on Object Detection in Optical Remote Sensing Images

Sun, X., Cheng, G., Pei, L., Li, H., & Han, J. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3273287 · Cited by 49

Category-Oriented Localization Distillation for SAR Object Detection and a Unified Benchmark

Wang, C., Ruan, R., Zhao, Z., Li, C., & Tang, J. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3291356 · Cited by 53

PIDray: A Large-Scale X-ray Benchmark for Real-World Prohibited Item Detection

Zhang, L., Jiang, L., Ji, R., & Fan, H. (2023) · International Journal of Computer Vision · doi:10.1007/s11263-023-01855-1 · Cited by 54

MonoGAE: Roadside Monocular 3D Object Detection With Ground-Aware Embeddings

Yang, L., Zhang, X., Yu, J., Li, J., Zhao, T., Wang, L., Huang, Y., Zhang, C., Wang, H., & Li, Y. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3412759 · Cited by 52

FreeKD: Knowledge Distillation via Semantic Frequency Prompt

Zhang, Y., Huang, T., Liu, J., Jiang, T., Cheng, K., & Zhang, S. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01508 · Cited by 55

CenterNet3D: An Anchor Free Object Detector for Point Cloud

Wang, G., Wu, J., Tian, B., Teng, S., Chen, L. F., & Cao, D. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3118698 · Cited by 77

PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling

Li, Y., Xu, Y., Wang, S., Yuan, C., Zhang, Z., Li, B., & Hu, W. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3193223 · Cited by 53

Rethinking Automatic Ship Wake Detection: State-of-the-Art CNN-Based Wake Detection via Optical Images

Xue, F., Jin, W., Qiu, S., & Yang, J. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3128989 · Cited by 46

A Scale-Aware Pyramid Network for Multi-Scale Object Detection in SAR Images

Tang, L., Tang, W., Qu, X., Han, Y., Wang, W., & Zhao, B. (2022) · Remote Sensing · doi:10.3390/rs14040973 · Cited by 54

RS-YOLOX: A High-Precision Detector for Object Detection in Satellite Remote Sensing Images

Yang, L., Yuan, G., Zhou, H., Liu, H., Chen, J., & Wu, H. (2022) · Applied Sciences · doi:10.3390/app12178707 · Cited by 48

Distribution-Aware Single-Stage Models for Multi-Person 3D Pose Estimation

Wang, Z., Nie, X., Qu, X., Chen, Y., & Liu, S. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01275 · Cited by 46

Omni-DETR: Omni-Supervised Object Detection with Transformers

Wang, P., Cai, Z., Yang, H., Swaminathan, G., Vasconcelos, N. M., Schiele, B., & Soatto, S. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00915 · Cited by 49

Tiny object detection model based on competitive multi-layer neural network (TOD-CMLNN)

Chirgaiya, S., & Rajavat, A. (2023) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2023.200217 · Cited by 46

ETAM: Ensemble transformer with attention modules for detection of small objects

Zhang, J., Xia, K., Huang, Z., Wang, S., & Akindele, R. G. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.119997 · Cited by 46

BasicTAD: An astounding RGB-Only baseline for temporal action detection

Yang, M., Chen, G., Zheng, Y.-D., Lü, T., & Wang, L. (2023) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2023.103692 · Cited by 49

Boosting Object Detectors via Strong-Classification Weak-Localization Pretraining in Remote Sensing Imagery

Zhang, C., Liu, T., Xiao, J., Lam, K., & Wang, Q. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3315392 · Cited by 46

Stereo Vision Meta-Lens-Assisted Driving Vision

Liu, X., Li, W., Yamaguchi, T., Geng, Z., Tanaka, T., Tsai, D. P., & Chen, M. K. (2024) · ACS Photonics · doi:10.1021/acsphotonics.3c01594 · Cited by 46

Review of Federated Learning and Machine Learning-Based Methods for Medical Image Analysis

Hernandez-Cruz, N., Saha, P., Sarker, M. M. K., & Noble, J. A. (2024) · Big Data and Cognitive Computing · doi:10.3390/bdcc8090099 · Cited by 51

Sparse Semi-DETR: Sparse Learnable Queries for Semi-Supervised Object Detection

Shehzadi, T., Hashmi, K. A., Stricker, D., & Afzal, M. Z. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.00558 · Cited by 46

Point2RBox: Combine Knowledge from Synthetic Visual Patterns for End-to-End Oriented Object Detection with Single Point Supervision

Yu, Y., Yang, X., Li, Q., Da, F., Dai, Y., Qiao, Y., & Yan, J. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01588 · Cited by 53

Scattering Enhancement and Feature Fusion Network for Aircraft Detection in SAR Images

Huang, B., Zhang, T., Quan, S., Wang, W., Guo, W., & Zhang, Z. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3470790 · Cited by 51

SOD-YOLO: A lightweight small object detection framework

Xiao, Y., & Di, N. (2024) · Scientific Reports · doi:10.1038/s41598-024-77513-4 · Cited by 52

A quantitative detection algorithm based on improved faster R-CNN for marine benthos

Liu, Y., & Wang, S. (2021) · Ecological Informatics · doi:10.1016/j.ecoinf.2021.101228 · Cited by 46

Object Detection in Remote Sensing Images via Multi-Feature Pyramid Network with Receptive Field Block

Yuan, Z., Liu, Z., Zhu, C., Qi, J., & Zhao, D. (2021) · Remote Sensing · doi:10.3390/rs13050862 · Cited by 47

Adaptive multi-level feature fusion and attention-based network for arbitrary-oriented object detection in remote sensing imagery

Chen, L., Liu, C., Chang, F., Li, S., & Nie, Z. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.04.011 · Cited by 46

Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection

Wang, T., Yang, T., Cao, J., & Zhang, X. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i4.16385 · Cited by 46

Artificial Intelligence in Chest Radiography Reporting Accuracy

Rudolph, J., Huemmer, C., Ghesu, F., Mansoor, A., Preuhs, A., Fieselmann, A., Fink, N., Dinkel, J., Koliogiannis, V., Schwarze, V., et al. (2021) · Investigative Radiology · doi:10.1097/rli.0000000000000813 · Cited by 45

Mutual Supervision for Dense Object Detection

Gao, Z., Wang, L., & Wu, G. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00362 · Cited by 47

Optimized convolutional neural network architectures for efficient on-device vision-based object detection

Rodríguez, I., Campos, C., & Fdez‐Riverola, F. (2021) · Neural Computing and Applications · doi:10.1007/s00521-021-06830-w · Cited by 50

Rank & Sort Loss for Object Detection and Instance Segmentation

Öksüz, K., Çam, B. C., Akbaş, E., & Kalkan, S. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00300 · Cited by 54

Reconcile Prediction Consistency for Balanced Object Detection

Wang, K., & Zhang, L. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00361 · Cited by 45

LSSNet

Yu, W.-W., Jiang, J., & Li, Y. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3479215 · Cited by 46

Polygon-to-Polygon Distance Loss for Rotated Object Detection

Yang, Y., Chen, J., Zhong, X., & Deng, Y. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i3.20214 · Cited by 46

Fusing mmWave Radar With Camera for 3-D Detection in Autonomous Driving

Liu, Y., Chang, S., Wei, Z., Zhang, K., & Feng, Z. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3175375 · Cited by 45

Single stage architecture for improved accuracy real-time object detection on mobile devices

Bacea, D.-S., & Oniga, F. (2022) · Image and Vision Computing · doi:10.1016/j.imavis.2022.104613 · Cited by 48

A Comprehensive Review of Modern Object Segmentation Approaches

Wang, Y., Ahsan, U., Li, H., & Hagen, M. (2022) · Foundations and Trends® in Computer Graphics and Vision · doi:10.1561/0600000097 · Cited by 54

DDOD: Dive Deeper into the Disentanglement of Object Detector

Chen, Z., Yang, C., Chang, J., Zhao, F., Zha, Z.-J., & Wu, F. H. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3264008 · Cited by 46

Obstacle Detection System for Navigation Assistance of Visually Impaired People Based on Deep Learning Techniques

Said, Y., Atri, M., Albahar, M. A., Atitallah, A. B., & Alsariera, Y. A. (2023) · Sensors · doi:10.3390/s23115262 · Cited by 45

Focal-PETR: Embracing Foreground for Efficient Multi-Camera 3D Object Detection

Wang, S., Jiang, X., & Li, Y. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3332608 · Cited by 51

SRT-Net: Scattering Region Topology Network for Oriented Ship Detection in Large-Scale SAR Images

Pan, D., Gao, X., Dai, W., Fu, J., Wang, Z., Sun, X., & Wu, Y. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3351366 · Cited by 45

Gradient Calibration Loss for Fast and Accurate Oriented Bounding Box Regression

Ming, Q., Miao, L., Zhou, Z., Song, J., & Pižurica, A. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3367294 · Cited by 48

Global–Local Feature Fusion Network for Visible–Infrared Vehicle Detection

Kang, X., Yin, H., & Duan, P. (2024) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2024.3375634 · Cited by 45

Challenges for Monocular 6-D Object Pose Estimation in Robotics

Thalhammer, S., Bauer, D., Hönig, P., Weibel, J.-B., García‐Rodríguez, J., & Vincze, M. (2024) · IEEE Transactions on Robotics · doi:10.1109/tro.2024.3433870 · Cited by 56

DiffusionTrack: Point Set Diffusion Model for Visual Object Tracking

Xie, F., Wang, Z., & Ma, C. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01808 · Cited by 58

SaccadeNet: A Fast and Accurate Object Detector

Lan, S., Ren, Z., Wu, Y., Davis, L. S., & Hua, G. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01041 · Cited by 45

One Metric to Measure Them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks

Öksüz, K., Çam, B. C., Kalkan, S., & Akbaş, E. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3130188 · Cited by 49

Deep Learning-Based Computer Vision for Surveillance in ITS: Evaluation of State-of-the-Art Methods

Xie, J., Zheng, Y., Du, R., Xiong, W., Cao, Y., Ma, Z., Cao, D., & Guo, J. H. (2021) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2021.3065250 · Cited by 45

Evaluation of dimensionality reduction methods for individual tree crown delineation using instance segmentation network and UAV multispectral imagery in urban forest

Xi, X., Xia, K., Yang, Y., Du, X., & Feng, H. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2021.106506 · Cited by 45

SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking

Peng, J., Jiang, Z., Gu, Y., Wu, Y., Wang, Y., Tai, Y. Y., Wang, C., & Lin, W. (2021) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2021/132 · Cited by 47

Multi-Source Aggregation Transformer for Concealed Object Detection in Millimeter-Wave Images

Sun, P., Liu, T., Chen, X., Zhang, S., Zhao, Y., & Wei, S. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3161815 · Cited by 48

A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images

Han, W., Li, J., Wang, S., Wang, Y., Yan, J., Fan, R., Zhang, X., & Wang, L. (2022) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2022.102966 · Cited by 45

Bridge coating inspection based on two-stage automatic method and collision-tolerant unmanned aerial system

Jiang, S., Wu, Y. Q., & Zhang, J. (2022) · Automation in Construction · doi:10.1016/j.autcon.2022.104685 · Cited by 44

Boosting target-level infrared and visible image fusion with regional information coordination

Han, M., Yu, K., Qiu, J., Li, H., Wu, D., Rao, Y., Yang, Y., Xing, L., Bai, H., & Zhou, C. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.12.005 · Cited by 44

An Improved FCOS Method for Ship Detection in SAR Images

Yang, S., An, W., Li, S., Wei, G., & Zou, B. (2022) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2022.3213583 · Cited by 44

Recent Few-shot Object Detection Algorithms: A Survey with Performance Comparison

Liu, T., Zhang, L., Wang, Y., Guan, J., Fu, Y., Zhao, J., & Zhou, S. (2023) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3593588 · Cited by 47

AdaDet: An Adaptive Object Detection System Based on Early-Exit Neural Networks

Yang, L., Zheng, Z., Wang, J., Song, S., Huang, G. M., & Li, F. (2023) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2023.3274214 · Cited by 46

Panicle-Cloud: An Open and AI-Powered Cloud Computing Platform for Quantifying Rice Panicles from Drone-Collected Imagery to Enable the Classification of Yield Production in Rice

Teng, Z., Chen, J., Wang, J., Wu, S., Chen, R., Lin, Y., Shen, L., Jackson, R. J., Zhou, J., & Yang, C. (2023) · Plant Phenomics · doi:10.34133/plantphenomics.0105 · Cited by 44

Efficient YOLOv7-Drone: An Enhanced Object Detection Approach for Drone Aerial Imagery

Fu, X., Wei, G., Yuan, X., Liang, Y., & Bo, Y. (2023) · Drones · doi:10.3390/drones7100616 · Cited by 44

DSAA-YOLO: UAV remote sensing small target recognition algorithm for YOLOV7 based on dense residual super-resolution and anchor frame adaptive regression strategy

Hui, Y., Wang, J., & Li, B. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101863 · Cited by 46

Pest-PVT: A model for multi-class and dense pest detection and counting in field-scale environments

Chen, H., Wen, C., Zhang, L., Ma, Z., Liu, T., Wang, G., Yu, H., Yang, C., Yuan, X., & Ren, J. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.109864 · Cited by 44

Dynamic frequency selection and spatial interaction fusion for robust person search

Zhang, Q., Miao, D., Zhang, Q., Zhao, C., Zhang, H., Sun, Y., & Wang, R. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103314 · Cited by 44

Multi-Scale and Occlusion Aware Network for Vehicle Detection and Segmentation on UAV Aerial Images

Zhang, W., Liu, C., Chang, F., & Song, Y. (2020) · Remote Sensing · doi:10.3390/rs12111760 · Cited by 44

Lemon‐YOLO: An efficient object detection method for lemons in the natural environment

Li, G., Huang, X., Ai, J., Yi, Z., & Xie, W. C. (2021) · IET Image Processing · doi:10.1049/ipr2.12171 · Cited by 46

Small Object Detection in Traffic Scenes Based on YOLO-MXANet

He, X., Cheng, R., Zheng, Z., & Wang, Z. (2021) · Sensors · doi:10.3390/s21217422 · Cited by 46

Cross-Connected Bidirectional Pyramid Network for Infrared Small-Dim Target Detection

Bai, Y., Li, R., Gou, S., Zhang, C., Chen, Y., & Zheng, Z. (2022) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2022.3145577 · Cited by 44

Fast ship detection based on lightweight YOLOv5 network

Zheng, J., Sun, S., & Zhao, S. (2022) · IET Image Processing · doi:10.1049/ipr2.12432 · Cited by 44

GCBANet: A Global Context Boundary-Aware Network for SAR Ship Instance Segmentation

Ke, X., Zhang, X., & Zhang, T. (2022) · Remote Sensing · doi:10.3390/rs14092165 · Cited by 46

FCOS: A Simple and Strong Anchor-free Object Detector

Tian, Z., Shen, C., Chen, H., & He, T. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3032166 · Cited by 972

A fully convolutional anchor-free object detector

Zhang, T., Li, Z., Sun, Z., & Zhu, L. (2022) · The Visual Computer · doi:10.1007/s00371-021-02357-2 · Cited by 9

EfficientFCOS: An Efficient One-stage Object Detection Model based on FCOS

Chu, Y., Guo, J., Shan, W., & Wang, Z. (2022) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd54268.2022.9776033 · Cited by 2

AugFCOS: Augmented fully convolutional one-stage object detection network

Zhang, X., Guo, W., Xing, Y., Wang, W., Yin, H., & Zhang, Y. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.109098 · Cited by 33

An Improved Anchor-Free Object Detection Method

Yu, H., Ding, T., Li, T., & Li, M. (2022) · International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) · doi:10.1109/mlise57402.2022.00009 · Cited by 5